This is a simple data analysis and visualization project using Python to study the relationship between car speed and driving risk. The project demonstrates how increasing speed correlates with higher risk, using scatter plots and basic machine learning preparation.
The dataset is a CSV file named car driving risk analysis.csv, containing two columns:
speed: Speed of the car (in km/h)risk: Associated risk value (arbitrary scale from 0 to 100)
Example:
| speed | risk |
|---|---|
| 200 | 95 |
| 90 | 20 |
| 300 | 98 |
| ... | ... |
Make sure you have the following Python libraries installed:
pip install numpy pandas matplotlib scikit-learn